SCADA-Based Reliability Evaluation

Kelmarsh Wind Farm - 12.3 MW

Kelmarsh Wind Farm

Project Overview

“Kelmarsh comprises six 2.05MW Senvion MM92 turbines. The Project was acquired from EON in December 2014 and was constructed in joint venture with Santander using balance sheet finance. Construction was completed in April 2016. It is now owned by Cubico Investments.”

• https://www.blue-energyco.com/our-projects/kelmarsh/

(a) Kelmarsh Wind Farm

(b) Senvion MM92 turbine

Figure 1: Kelmarsh Wind Farm is located near Haselbach, Northamptonshire, UK.

Events Catalogue

IEC category	Events
Technical Standby	59342
Requested Shutdown	77
Out of Environmental Specification	90593
Forced outage	1295
None	3253
Out of Electrical Specification	371
Scheduled Maintenance	818
Full Performance	229338
Partial Performance	46

Only events labeled as “Forced outage” with Status “Stop” will be considered for the reliability analysis of the Senvion wind turbines, highlighting the very stochastic nature of failure occurrences caused by hardware.

Status	Qty
Stop	892
Warning	403
Warning	1461
Informational	227877
Stop	371
Informational	90500
Stop	93
Curtailment	37
Warning	9
Stop	77
Stop	818
Stop	3094
Informational	56248
Warning	2320
Informational	168
Communication	744
Stop	21

shape: (7, 2)

IEC category	Stop_Events
str	u32
"Scheduled Maintenance"	818
"Forced outage"	892
"Out of Environmental Specifica…	93
"Technical Standby"	3094
"Requested Shutdown"	77
"Out of Electrical Specificatio…	371
null	21

<bound method DataFrame.head of shape: (1_779, 7)
┌─────────────────────────┬────────┬───────────────────────────────┬─────┬───────┬──────┬──────────┐
│ Timestamp               ┆ Status ┆ Message                       ┆ wt  ┆ State ┆ Year ┆ Year_wt  │
│ ---                     ┆ ---    ┆ ---                           ┆ --- ┆ ---   ┆ ---  ┆ ---      │
│ datetime[μs, UTC]       ┆ str    ┆ str                           ┆ str ┆ i32   ┆ i32  ┆ str      │
╞═════════════════════════╪════════╪═══════════════════════════════╪═════╪═══════╪══════╪══════════╡
│ 2016-01-14 19:28:03 UTC ┆ Stop   ┆ Emergency stop nacelle        ┆ T01 ┆ 0     ┆ 2016 ┆ 2016-T01 │
│ 2016-01-23 14:36:32 UTC ┆ Start  ┆ Emergency stop nacelle        ┆ T01 ┆ 1     ┆ 2016 ┆ 2016-T01 │
│ 2016-01-23 15:05:30 UTC ┆ Stop   ┆ Emergency stop base box       ┆ T01 ┆ 0     ┆ 2016 ┆ 2016-T01 │
│ 2016-01-23 15:06:42 UTC ┆ Start  ┆ Emergency stop base box       ┆ T01 ┆ 1     ┆ 2016 ┆ 2016-T01 │
│ 2016-01-24 16:51:17 UTC ┆ Stop   ┆ Frequency converter error     ┆ T01 ┆ 0     ┆ 2016 ┆ 2016-T01 │
│ …                       ┆ …      ┆ …                             ┆ …   ┆ …     ┆ …    ┆ …        │
│ 2022-07-11 13:48:21 UTC ┆ Start  ┆ Anemometer defect             ┆ T06 ┆ 1     ┆ 2022 ┆ 2022-T06 │
│ 2022-07-19 13:17:02 UTC ┆ Stop   ┆ Max.temp.conv.inl.>perm.out.t ┆ T06 ┆ 0     ┆ 2022 ┆ 2022-T06 │
│                         ┆        ┆ .                             ┆     ┆       ┆      ┆          │
│ 2022-07-19 18:11:27 UTC ┆ Start  ┆ Max.temp.conv.inl.>perm.out.t ┆ T06 ┆ 1     ┆ 2022 ┆ 2022-T06 │
│                         ┆        ┆ .                             ┆     ┆       ┆      ┆          │
│ 2022-11-02 17:39:07 UTC ┆ Stop   ┆ Manual stop - remote          ┆ T06 ┆ 0     ┆ 2022 ┆ 2022-T06 │
│ 2022-11-02 18:25:51 UTC ┆ Start  ┆ Manual stop - remote          ┆ T06 ┆ 1     ┆ 2022 ┆ 2022-T06 │
└─────────────────────────┴────────┴───────────────────────────────┴─────┴───────┴──────┴──────────┘>

Reliability Parameters

Six Wind Turbines - Model Senvion MM92
Reliability Evaluation (2016 - 2022)
	Turbine	Forced Outages		Failure Rate [h−1]	Ready *	State delete	Out-of-Service		year_end	year_start	duration_hours	Probabilities
		Total	Monthly		MTTF [h]		MTTR [h]	Duration [h]				FOR (P0)	Availability (P1)
2016
T01		32		0.00379	248.49	32	15.66	501.01	2016-12-31 23:59:59.000000+00:00	2016-01-14 19:28:03.000000+00:00	8452.53	0.05927	0.94073
T02		53		0.00627	156.47	52	2.89	153.18	2016-12-31 23:59:59.000000+00:00	2016-01-14 19:28:03.000000+00:00	8452.53	0.01814	0.98186
T03		30		0.00355	265.50	30	5.96	178.92	2016-12-31 23:59:59.000000+00:00	2016-01-14 19:28:03.000000+00:00	8452.53	0.02197	0.97803
T04		18		0.00213	439.29	18	2.33	41.90	2016-12-31 23:59:59.000000+00:00	2016-01-14 19:28:03.000000+00:00	8452.53	0.00527	0.99473
T05		17		0.00201	457.36	17	25.98	441.71	2016-12-31 23:59:59.000000+00:00	2016-01-14 19:28:03.000000+00:00	8452.53	0.05376	0.94624
T06		29		0.00343	266.34	29	6.33	183.64	2016-12-31 23:59:59.000000+00:00	2016-01-14 19:28:03.000000+00:00	8452.53	0.02322	0.97678
2017
T01		24		0.00274	348.69	25	1.78	42.66	2017-12-31 23:59:59.000000+00:00	2017-01-01 00:00:00.000000+00:00	8760.0	0.00507	0.99493
T02		17		0.00194	486.26	18	0.43	7.28	2017-12-31 23:59:59.000000+00:00	2017-01-01 00:00:00.000000+00:00	8760.0	0.00088	0.99912
T03		9		0.00103	875.63	10	0.41	3.73	2017-12-31 23:59:59.000000+00:00	2017-01-01 00:00:00.000000+00:00	8760.0	0.00047	0.99953
T04		21		0.00240	397.92	22	0.28	5.85	2017-12-31 23:59:59.000000+00:00	2017-01-01 00:00:00.000000+00:00	8760.0	0.00070	0.99930
T05		14		0.00160	583.60	15	0.43	6.07	2017-12-31 23:59:59.000000+00:00	2017-01-01 00:00:00.000000+00:00	8760.0	0.00074	0.99926
T06		37		0.00422	221.54	39	3.24	119.79	2017-12-31 23:59:59.000000+00:00	2017-01-01 00:00:00.000000+00:00	8760.0	0.01440	0.98560
2018
T01		12		0.00137	673.55	13	0.32	3.84	2018-12-31 23:59:59.000000+00:00	2018-01-01 00:00:00.000000+00:00	8760.0	0.00047	0.99953
T02		19		0.00217	437.37	20	0.66	12.56	2018-12-31 23:59:59.000000+00:00	2018-01-01 00:00:00.000000+00:00	8760.0	0.00151	0.99849
T03		24		0.00274	349.98	25	0.44	10.45	2018-12-31 23:59:59.000000+00:00	2018-01-01 00:00:00.000000+00:00	8760.0	0.00124	0.99876
T04		11		0.00126	729.18	12	0.90	9.87	2018-12-31 23:59:59.000000+00:00	2018-01-01 00:00:00.000000+00:00	8760.0	0.00123	0.99877
T05		11		0.00126	726.26	12	4.08	44.86	2018-12-31 23:59:59.000000+00:00	2018-01-01 00:00:00.000000+00:00	8760.0	0.00558	0.99442
T06		19		0.00217	416.82	21	0.35	6.71	2018-12-31 23:59:59.000000+00:00	2018-01-01 00:00:00.000000+00:00	8760.0	0.00085	0.99915
2019
T01		15		0.00171	546.96	16	0.58	8.63	2019-12-31 23:59:59.000000+00:00	2019-01-01 00:00:00.000000+00:00	8760.0	0.00105	0.99895
T02		17		0.00194	485.38	18	1.36	23.18	2019-12-31 23:59:59.000000+00:00	2019-01-01 00:00:00.000000+00:00	8760.0	0.00280	0.99720
T03		10		0.00114	794.45	11	2.11	21.06	2019-12-31 23:59:59.000000+00:00	2019-01-01 00:00:00.000000+00:00	8760.0	0.00264	0.99736
T04		17		0.00194	486.21	18	0.48	8.20	2019-12-31 23:59:59.000000+00:00	2019-01-01 00:00:00.000000+00:00	8760.0	0.00099	0.99901
T05		8		0.00091	972.48	9	0.96	7.66	2019-12-31 23:59:59.000000+00:00	2019-01-01 00:00:00.000000+00:00	8760.0	0.00098	0.99902
T06		9		0.00103	791.37	11	6.11	54.96	2019-12-31 23:59:59.000000+00:00	2019-01-01 00:00:00.000000+00:00	8760.0	0.00766	0.99234
2020
T01		21		0.00239	397.40	22	1.97	41.31	2020-12-31 23:59:59.000000+00:00	2020-01-01 00:00:00.000000+00:00	8784.0	0.00493	0.99507
T02		25		0.00285	337.12	26	0.76	18.92	2020-12-31 23:59:59.000000+00:00	2020-01-01 00:00:00.000000+00:00	8784.0	0.00224	0.99776
T03		14		0.00159	580.58	15	5.37	75.25	2020-12-31 23:59:59.000000+00:00	2020-01-01 00:00:00.000000+00:00	8784.0	0.00917	0.99083
T04		30		0.00342	281.19	31	2.23	66.99	2020-12-31 23:59:59.000000+00:00	2020-01-01 00:00:00.000000+00:00	8784.0	0.00788	0.99212
T05		16		0.00182	515.19	17	1.61	25.69	2020-12-31 23:59:59.000000+00:00	2020-01-01 00:00:00.000000+00:00	8784.0	0.00311	0.99689
T06		24		0.00273	337.27	26	0.62	14.88	2020-12-31 23:59:59.000000+00:00	2020-01-01 00:00:00.000000+00:00	8784.0	0.00184	0.99816
2021
T01		24		0.00274	345.82	25	4.77	114.53	2021-12-31 23:59:59.000000+00:00	2021-01-01 00:00:00.000000+00:00	8760.0	0.01361	0.98639
T02		14		0.00160	583.82	15	0.19	2.71	2021-12-31 23:59:59.000000+00:00	2021-01-01 00:00:00.000000+00:00	8760.0	0.00033	0.99967
T03		12		0.00137	673.70	13	0.16	1.95	2021-12-31 23:59:59.000000+00:00	2021-01-01 00:00:00.000000+00:00	8760.0	0.00024	0.99976
T04		10		0.00114	796.26	11	0.12	1.15	2021-12-31 23:59:59.000000+00:00	2021-01-01 00:00:00.000000+00:00	8760.0	0.00014	0.99986
T05		27		0.00308	302.35	28	10.89	294.06	2021-12-31 23:59:59.000000+00:00	2021-01-01 00:00:00.000000+00:00	8760.0	0.03477	0.96523
T06		13		0.00148	576.61	15	8.53	110.83	2021-12-31 23:59:59.000000+00:00	2021-01-01 00:00:00.000000+00:00	8760.0	0.01457	0.98543
2022
T01		85		0.00970	101.61	86	0.26	21.94	2022-12-31 23:59:59.000000+00:00	2022-01-01 00:00:00.000000+00:00	8760.0	0.00253	0.99747
T02		33		0.00377	255.89	34	1.81	59.77	2022-12-31 23:59:59.000000+00:00	2022-01-01 00:00:00.000000+00:00	8760.0	0.00703	0.99297
T03		7		0.00080	1,094.54	8	0.53	3.71	2022-12-31 23:59:59.000000+00:00	2022-01-01 00:00:00.000000+00:00	8760.0	0.00048	0.99952
T04		9		0.00103	869.82	10	6.86	61.75	2022-12-31 23:59:59.000000+00:00	2022-01-01 00:00:00.000000+00:00	8760.0	0.00783	0.99217
T05		34		0.00388	250.05	35	0.25	8.37	2022-12-31 23:59:59.000000+00:00	2022-01-01 00:00:00.000000+00:00	8760.0	0.00098	0.99902
T06		18		0.00205	438.48	19	23.83	428.91	2022-12-31 23:59:59.000000+00:00	2022-01-01 00:00:00.000000+00:00	8760.0	0.05154	0.94846
* Forced Outages (IEC) only, scheduled stops not included.

Time / State Diagrams

2016

2017

2018

2019

2020

2021

2022

Histogram of Failure Causes

Total

Per Wind Turbine

References

Iannone, Richard, and Michael Chow. n.d. “great-tables: Make awesome display tables using Python.” https://github.com/posit-dev/great-tables.

Mühleisen, Hannes, Mark Raasveldt, et al. 2025. “DuckDB: An Embeddable Analytical Database.” https://duckdb.org.

Plumley, Charlie. 2022. “Kelmarsh Wind Farm Data (0.1.0) [Data Set].” Zenodo. https://zenodo.org/records/8252025.

Vink, Ritchie, and contributors. 2025. “Polars: Fast Multi-Threaded DataFrame Library in Rust and Python.” https://www.pola.rs/.